Electronic Health Record (EHR) systems improve patient care by reducing redundancy in prescribing and computerized ordering but paradoxically also generate other types of information redundancy that lead to information overload. This presents a challenge for clinicians in providing safe and effective care especially with complex patients requiring synthesis of many clinical elements across a lengthy medical history. We hypothesize that provider usage of clinical notes can be supported through refinement of automated methods to detect new information, facilitation of new information visualization in practice, and EHR clinical note interface optimization. While there is much interest in supporting evidence-based medicine, little attention has been given to assisting clinicians in navigating and synthesizing growing amounts of electronic data for individual patients. Unstructured narrative text is an important part of modern EHRs. Text allows clinicians to communicate complex and nuanced information in a manner that is easily comprehended by others. While analyzing a collection of patient's notes can be formidable, it is necessary for making diagnostic and therapeutic decisions. Currently, this process is hindered by many factors, including large amounts of redundant information in these texts, increasing numbers of documents, suboptimal user interface (UI) design, and limited time to interact with patients. There is a critical need to optimize the use of EHR clinical notes for providers, which we propose to address in three aims: 1) Refine computational methods to identify new information in clinical notes, 2) Assess the effect of visualizing new information in clinical notes in an inpatient hospitalist setting, and 3) Discover elements of a rationally designed EHR graphical UI to facilitate clinical document usage in practice. Successful accomplishment of these aims will lay a foundation to make clinicians more efficient, improve decision-making, decrease cognitive load, and potentially increase clinician satisfaction associated with using clinical documents in EHR systems.